Hourly Forecasting of Solar Photovoltaic Power in Pakistan Using Recurrent Neural Networks

Table 3

Hourly forecast of PV power output using LSTM and Bi-LSTM, RMSE, square, and Cv (RMSE) of the respective model.

Weather	Model	RMSE	square	Cv (RMSE) %
Sunny	LSTM (2 layers)	0.06	0.99	0.15
	Bi LSTM	0.06	0.99	0.15
Cloudy	LSTM (2 layers)	0.058	0.99	0.21
	Bi LSTM	0.0025	0.99	0.0095
Rainy	LSTM (2 layers)	0.157	0.91	0.60
	Bi LSTM	0.12	0.95	0.54
Partial cloudy	LSTM (2 layers)	0.18	0.81	0.51
	Bi LSTM	0.06	0.99	0.17
Dusty	LSTM (2 layers)	0.18	0.80	0.50
	Bi LSTM	0.08	0.99	0.22
Fog	LSTM (2 layers)	0.17	0.85	0.84
	Bi LSTM	0.072	0.98	0.33